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   <div id="projectname">Parallel Gaussian Process Regression
   &#160;<span id="projectnumber">1.0.0</span>
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   <div id="projectbrief">The implementation of parallel Gaussian process (GP) regression is based on the following publication: Jie Chen, Nannan Cao, Kian Hsiang Low, Ruofei Ouyang, Colin Keng-Yan Tan &amp; Patrick Jaillet. Parallel Gaussian Process Regression with Low-Rank Covariance Matrix Approximations. In Proceedings of the 29th Conference on Uncertainty in Artificial Intelligence (UAI 2013), Bellevue, WA, Jul 11-15, 2013.</div>
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<p>This file provides functionalities to parse commandlines of different applications and domain files.  
<a href="#details">More...</a></p>
<div class="textblock"><code>#include &quot;<a class="el" href="pgpr__type_8h_source.html">pgpr_type.h</a>&quot;</code><br />
<code>#include &quot;<a class="el" href="pgpr__util_8h_source.html">pgpr_util.h</a>&quot;</code><br />
</div>
<p><a href="pgpr__parse_8h_source.html">Go to the source code of this file.</a></p>
<table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="nested-classes"></a>
Classes</h2></td></tr>
<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">struct &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="structt__command__prep.html">t_command_prep</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Information parsed from commandline of application that prepares the experimental data.  <a href="structt__command__prep.html#details">More...</a><br /></td></tr>
<tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">struct &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="structt__command__demo.html">t_command_demo</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Information parsed from commandline of application that demonstrates the regression algorithms.  <a href="structt__command__demo.html#details">More...</a><br /></td></tr>
<tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpgpr__parse.html">pgpr_parse</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">This class parses domain data files, configuration file and commandline of different applications.  <a href="classpgpr__parse.html#details">More...</a><br /></td></tr>
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<a name="details" id="details"></a><h2 class="groupheader">Detailed Description</h2>
<div class="textblock"><p>This file provides functionalities to parse commandlines of different applications and domain files. </p>
<p>In this version, this class support parsing two type of applications: 1. preparing data for experiment; 2. demonstration of regression algorithms. In addition, this class can load and parse domain files which includs a file storing the domain inputs and outputs (features and targets), and a configuration file containing basic information of the domain.</p>
<dl class="section author"><dt>Author</dt><dd>CHEN jie, <a href="#" onclick="location.href='mai'+'lto:'+'ari'+'k.'+'cj@'+'gm'+'ail'+'.c'+'om'; return false;">arik.<span style="display: none;">.nosp@m.</span>cj@g<span style="display: none;">.nosp@m.</span>mail.<span style="display: none;">.nosp@m.</span>com</a></dd></dl>
<dl class="section version"><dt>Version</dt><dd>1.0 </dd></dl>
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